1. Field of the Invention
The present invention relates to image processing, and more particularly to techniques providing image enhancement and thresholding of images.
2. Description of Related Art
There are numerous situations in which it would be desirable to be able to enhance the quality of images (for example, from cameras found in video-conferencing systems) which are stored, communicated and/or processed in (digital) electronic form. Also, such enhancement is desirable in order to produce efficient and high quality video scanning of document images in over-the-desk scanning systems such as those disclosed in EP-A-622,722 and British patent application 9614694.9: these patent applications describe systems employing a video camera disposed above a desk and capturing images of documents which are displayed to a user.
Over-the-desk scanning with video cameras has many advantages over traditional scanning techniques, as discussed in some detail in the aforementioned patent applications.
A problem that that arises in the aforementioned systems is that of how to convert the images from the document camera to a form as close to the original paper image as possible. An obvious disadvantage with the scanners used in those systems is the poor resolution of existing TV cameras, which will only provide 100 dpi (dots/inch) (4 dots/mm) greyscale over a desk-top footprint of 4".times.3" (100 mm.times.75 mm) (or about a quarter of a page).
Numerous thresholding algorithms of varying degrees of complexity are known. Mitchel, J. et. al. "Graphics Image Coding for Freeze-Frame Videoconferencing," IEEE Trans. on Comms., Vol. 37, No. 5, May 1989 consider the problem of document image coding for freeze-frame video conferencing. They map an 8 bits per pixel (bpp) image to 3 bpp which achieves their goal of increased coding efficiency. They do not generate a higher resolution binary image.
There is a need for image processing methods and systems able to generate high-resolution binary images so that traditional document image decoding algorithms involving morphological operations and connected component analysis may be used. In short, there is a need for computationally efficient conversion of low resolution greyscale images to higher resolution binary images, for example of documents in the desk-top environment.